mlr_resamplings_repeated_spcv_disc function

(sperrorest) Repeated spatial "disc" resampling

(sperrorest) Repeated spatial "disc" resampling

(sperrorest) Repeated spatial "disc" resampling

Parameters

• repeats (integer(1))

  Number of repeats.

Examples

library(mlr3)
task = tsk("ecuador")

# Instantiate Resampling
rrcv = rsmp("repeated_spcv_disc",
  folds = 3L, repeats = 2,
  radius = 200L, buffer = 200L)
rrcv$instantiate(task)

# Individual sets:
rrcv$iters
rrcv$folds(1:6)
rrcv$repeats(1:6)

# Individual sets:
rrcv$train_set(1)
rrcv$test_set(1)
intersect(rrcv$train_set(1), rrcv$test_set(1))

# Internal storage:
rrcv$instance # table

References

Brenning A (2012). Spatial cross-validation and bootstrap for the assessment of predictionrules in remote sensing: The R package sperrorest.

In 2012 IEEE International Geoscience and Remote Sensing Symposium. tools:::Rd_expr_doi("10.1109/igarss.2012.6352393") .

Super class

mlr3::Resampling -> ResamplingRepeatedSpCVDisc

Active bindings

• iters: integer(1)

   Returns the number of resampling iterations, depending on the values stored in the `param_set`.
  

Methods

Public methods

• list("ResamplingRepeatedSpCVDisc$new()")

• list("ResamplingRepeatedSpCVDisc$folds()")

• list("ResamplingRepeatedSpCVDisc$repeats()")

• list("ResamplingRepeatedSpCVDisc$instantiate()")

• list("ResamplingRepeatedSpCVDisc$clone()")

Method new()

Create a "Spatial 'Disc' resampling" resampling instance.

For a list of available arguments, please see sperrorest::partition_disc .

Usage

ResamplingRepeatedSpCVDisc$new(id = "repeated_spcv_disc")

Arguments

• id: character(1)

   Identifier for the resampling strategy.
  

Method folds()

Translates iteration numbers to fold number.

Usage

ResamplingRepeatedSpCVDisc$folds(iters)

Arguments

• iters: integer()

   Iteration number.
  

Method repeats()

Translates iteration numbers to repetition number.

Usage

ResamplingRepeatedSpCVDisc$repeats(iters)

Arguments

• iters: integer()

   Iteration number.
  

Method instantiate()

Materializes fixed training and test splits for a given task.

Usage

ResamplingRepeatedSpCVDisc$instantiate(task)

Arguments

• task: mlr3::Task

   A task to instantiate.
  

Method clone()

The objects of this class are cloneable with this method.

Usage

ResamplingRepeatedSpCVDisc$clone(deep = FALSE)

Arguments

• deep: Whether to make a deep clone.